{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "83bbedd0-eb58-48de-992e-484071b10104",
   "metadata": {},
   "source": [
    "# Web Scraper with JavaScript Support\n",
    "Uses day1-webscraping-selenium-for-javascript.ipynb solution simplified so easy to run.\n",
    "\n",
    "## Install dependencies\n",
    "Uncomment and run once"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2d91971-9dd0-4714-8ec7-f1fb25f95140",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install selenium\n",
    "# !pip install undetected-chromedriver\n",
    "# !ollama pull llama3.2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "967258fe-3296-464c-962d-2bcf821eae67",
   "metadata": {},
   "source": [
    "## Import required dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe8a87c8-0475-45a1-8ca2-fb9059e5470b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import requests\n",
    "from dotenv import load_dotenv\n",
    "from bs4 import BeautifulSoup\n",
    "from IPython.display import Markdown, display\n",
    "from openai import OpenAI\n",
    "import undetected_chromedriver as uc\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.support.ui import WebDriverWait\n",
    "from selenium.webdriver.support import expected_conditions as EC\n",
    "import time\n",
    "from bs4 import BeautifulSoup\n",
    "\n",
    "# If you get an error running this cell, then please head over to the troubleshooting notebook!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df60545e-2ab6-4e37-b41c-27ddf2affb92",
   "metadata": {},
   "source": [
    "## Run setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3846089-efa2-4602-8bc3-5f6f4945de64",
   "metadata": {},
   "outputs": [],
   "source": [
    "chrome_path = \"C:/Program Files/Google/Chrome/Application/chrome.exe\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b835812d-3692-4192-abc4-15fc463bd08f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load environment variables in a file called .env\n",
    "\n",
    "load_dotenv()\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "# Check the key\n",
    "\n",
    "if not api_key:\n",
    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
    "elif not api_key.startswith(\"sk-proj-\"):\n",
    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
    "elif api_key.strip() != api_key:\n",
    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
    "else:\n",
    "    print(\"API key found and looks good so far!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "acb89abb-dcee-4da6-98f8-e339d258f2a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "openai = OpenAI()\n",
    "\n",
    "# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
    "# If it STILL doesn't work (horrors!) then please see the troubleshooting notebook, or try the below line instead:\n",
    "# openai = OpenAI(api_key=\"your-key-here-starting-sk-proj-\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e860e963-e7a1-4888-a4b9-db9c24bb9a6e",
   "metadata": {},
   "source": [
    "# Create Prompts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4933c36-db8a-4333-8f81-e9db7ba41287",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\n",
    "\n",
    "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
    "and provides a short summary, ignoring text that might be navigation related. \\\n",
    "Respond in markdown.\"\n",
    "\n",
    "# A function that writes a User Prompt that asks for summaries of websites:\n",
    "\n",
    "def user_prompt_for(website):\n",
    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
    "    user_prompt += \"\\nThe contents of this website is as follows; \\\n",
    "please provide a short summary of this website in markdown. \\\n",
    "If it includes news or announcements, then summarize these too.\\n\\n\"\n",
    "    user_prompt += website.text\n",
    "    return user_prompt\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17cfab59-304d-4d2f-b324-c388d9e87fca",
   "metadata": {},
   "source": [
    "# Create Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca5e96e0-4d8f-49de-a608-a735a5b23b1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup for how OpenAI expects to receive messages in a particular structure\n",
    "\n",
    "def messages_for(website):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
    "    ]\n",
    "\n",
    "# Use Selenium and chrome to scrape website\n",
    "class WebsiteCrawler:\n",
    "    def __init__(self, url, wait_time=20, chrome_binary_path=None):\n",
    "        \"\"\"\n",
    "        Initialize the WebsiteCrawler using Selenium to scrape JavaScript-rendered content.\n",
    "        \"\"\"\n",
    "        self.url = url\n",
    "        self.wait_time = wait_time\n",
    "\n",
    "        options = uc.ChromeOptions()\n",
    "        options.add_argument(\"--disable-gpu\")\n",
    "        options.add_argument(\"--no-sandbox\")\n",
    "        options.add_argument(\"--disable-dev-shm-usage\")\n",
    "        options.add_argument(\"--disable-blink-features=AutomationControlled\")\n",
    "        options.add_argument(\"start-maximized\")\n",
    "        options.add_argument(\n",
    "            \"user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
    "        )\n",
    "        if chrome_binary_path:\n",
    "            options.binary_location = chrome_binary_path\n",
    "\n",
    "        self.driver = uc.Chrome(options=options)\n",
    "\n",
    "        try:\n",
    "            # Load the URL\n",
    "            self.driver.get(url)\n",
    "\n",
    "            # Wait for Cloudflare or similar checks\n",
    "            time.sleep(10)\n",
    "\n",
    "            # Ensure the main content is loaded\n",
    "            WebDriverWait(self.driver, self.wait_time).until(\n",
    "                EC.presence_of_element_located((By.TAG_NAME, \"main\"))\n",
    "            )\n",
    "\n",
    "            # Extract the main content\n",
    "            main_content = self.driver.find_element(By.CSS_SELECTOR, \"main\").get_attribute(\"outerHTML\")\n",
    "\n",
    "            # Parse with BeautifulSoup\n",
    "            soup = BeautifulSoup(main_content, \"html.parser\")\n",
    "            self.title = self.driver.title if self.driver.title else \"No title found\"\n",
    "            self.text = soup.get_text(separator=\"\\n\", strip=True)\n",
    "\n",
    "        except Exception as e:\n",
    "            print(f\"Error occurred: {e}\")\n",
    "            self.title = \"Error occurred\"\n",
    "            self.text = \"\"\n",
    "\n",
    "        finally:\n",
    "            self.driver.quit()\n",
    "\n",
    "def new_summary(url, chrome_path):\n",
    "    web = WebsiteCrawler(url, 30, chrome_path)\n",
    "    response = openai.chat.completions.create(\n",
    "            model = \"gpt-4o-mini\",\n",
    "            messages = messages_for(web)\n",
    "        )\n",
    "\n",
    "    web_summary = response.choices[0].message.content\n",
    "    \n",
    "    return display(Markdown(web_summary))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20a8a14b-0a29-4f74-a591-d587b965409b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\n",
    "\n",
    "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
    "and provides a short summary, ignoring text that might be navigation related. \\\n",
    "Respond in markdown.\"\n",
    "\n",
    "# A function that writes a User Prompt that asks for summaries of websites:\n",
    "\n",
    "def user_prompt_for(website):\n",
    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
    "    user_prompt += \"\\nThe contents of this website is as follows; \\\n",
    "please provide a short summary of this website in markdown. \\\n",
    "If it includes news or announcements, then summarize these too.\\n\\n\"\n",
    "    user_prompt += website.text\n",
    "    return user_prompt\n",
    "\n",
    "# Setup for how OpenAI expects to receive messages in a particular structure\n",
    "\n",
    "def messages_for(website):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
    "    ]\n",
    "\n",
    "# Use Selenium and chrome to scrape website\n",
    "class WebsiteCrawler:\n",
    "    def __init__(self, url, wait_time=20, chrome_binary_path=None):\n",
    "        \"\"\"\n",
    "        Initialize the WebsiteCrawler using Selenium to scrape JavaScript-rendered content.\n",
    "        \"\"\"\n",
    "        self.url = url\n",
    "        self.wait_time = wait_time\n",
    "\n",
    "        options = uc.ChromeOptions()\n",
    "        options.add_argument(\"--disable-gpu\")\n",
    "        options.add_argument(\"--no-sandbox\")\n",
    "        options.add_argument(\"--disable-dev-shm-usage\")\n",
    "        options.add_argument(\"--disable-blink-features=AutomationControlled\")\n",
    "        options.add_argument(\"start-maximized\")\n",
    "        options.add_argument(\n",
    "            \"user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
    "        )\n",
    "        if chrome_binary_path:\n",
    "            options.binary_location = chrome_binary_path\n",
    "\n",
    "        self.driver = uc.Chrome(options=options)\n",
    "\n",
    "        try:\n",
    "            # Load the URL\n",
    "            self.driver.get(url)\n",
    "\n",
    "            # Wait for Cloudflare or similar checks\n",
    "            time.sleep(10)\n",
    "\n",
    "            # Ensure the main content is loaded\n",
    "            WebDriverWait(self.driver, self.wait_time).until(\n",
    "                EC.presence_of_element_located((By.TAG_NAME, \"main\"))\n",
    "            )\n",
    "\n",
    "            # Extract the main content\n",
    "            main_content = self.driver.find_element(By.CSS_SELECTOR, \"main\").get_attribute(\"outerHTML\")\n",
    "\n",
    "            # Parse with BeautifulSoup\n",
    "            soup = BeautifulSoup(main_content, \"html.parser\")\n",
    "            self.title = self.driver.title if self.driver.title else \"No title found\"\n",
    "            self.text = soup.get_text(separator=\"\\n\", strip=True)\n",
    "\n",
    "        except Exception as e:\n",
    "            print(f\"Error occurred: {e}\")\n",
    "            self.title = \"Error occurred\"\n",
    "            self.text = \"\"\n",
    "\n",
    "        finally:\n",
    "            self.driver.quit()\n",
    "\n",
    "def new_summary(url, chrome_path):\n",
    "    web = WebsiteCrawler(url, 30, chrome_path)\n",
    "    response = openai.chat.completions.create(\n",
    "            model = \"gpt-4o-mini\",\n",
    "            messages = messages_for(web)\n",
    "        )\n",
    "\n",
    "    web_summary = response.choices[0].message.content\n",
    "    \n",
    "    return display(Markdown(web_summary))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5f974b3-e417-43a2-88f1-8db06096cd53",
   "metadata": {},
   "source": [
    "# Scrape and Summarize Web Page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55f240cb-1fca-46bf-81d1-1beeea64439d",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://www.canva.com/\"\n",
    "new_summary(url, chrome_path)"
   ]
  }
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